An Improved IDS Detection with Protection of Agent Collude Attacks
نویسندگان
چکیده
There are chances like a data distributor had given his sensitive data to a set of trusted agents. These agents can be called as third parties. There are chances that some of the data is leaked and found in an unauthorized place. This situation is called IDS. In existing case, the method called watermarking is using to identify the leakage. Or also uses the technique like injecting fake data that appears to be realistic in the data. I propose data allocation strategies that improve the probability of identifying leakages. In enhancement work I include the investigation of agent guilt models that capture leakage scenarios.
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